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1.
Asian Journal of Atmospheric Environment ; 16(1), 2022.
Article in English | Scopus | ID: covidwho-1732405

ABSTRACT

Malaysia reported its first COVID-19 case on January 25, 2020, and the cases have continued to grow, necessitating the implementation of additional measures. Hence, determining the factors responsible for the significant increase in COVID-19 cases is the top priority issue for the government to take necessary action and ultimately restrain this virus before the vaccine availability. Researchers had predicted that air pollution had an indirect relationship with COVID-19 in terms of virus infections. As a result, this study focuses on the link between the Air Pollutant Index (API) and COVID-19 infections. The initial data set consists of daily confirmed COVID-19 cases in Malaysia and API readings obtained from the Ministry of Health (MOH) and the Department of the Environment (DOE). The results show that Klang (S22) recorded the highest mean of API which at 62.70 while the lowest is at Limbang (S37) (25.37). Next, due to the implementation of Movement Control Order (MCO) in Malaysia and reducing social movement, 27 stations recorded a good level of API compare to the stations that recorded moderate and unhealthy levels. There is positive relationship between API and COVID-19 at each of the region which are North 0.4% (R2=0.004), Central 2.1% (R2=0.021), South 0.04% (R2=0.0004), East 1.6% (R2=0.016), Sarawak 0.2% (R2=0.002), meanwhile Sabah recorded negative correlation at 4.3% (R2=0.043). To conclude, the API value did not have a strong relationship with the rising number of COVID-19 daily cases © 2022 by Asian Association for Atmospheric Environment

2.
Malaysian Journal of Medicine and Health Sciences ; 17:42-50, 2021.
Article in English | Scopus | ID: covidwho-1573306

ABSTRACT

Introduction: This paper focuses on the epidemiological hotspot of COVID-19 cases in Malaysia and the population incidence rates under Movement Control Orders (MCOs). Methods: Dataset from the Ministry of Health Malaysia (MOH) were employed to determine the cumulative incidence rates by using population-based reference data from confirmed infections (cases/10,000 population) and the mapping was done by geographical information systems (GIS) software for three phases of MCOs (17th March - 28th April 2020) in Peninsular Malaysia. Results: The total number of COVID-19 cases reported by MCOs for 42 days was 4,580 and the incidence rate was 17.72 per 100,000 population. The trend of daily new COVID-19 cases reported across the MCOs was 1,949 cases in the first 14 days of the epidemic (MCO1) (the incidence rate of 7.54 per 100,000 population), 1,930 cases during MCO2 (incidence rate of 7.47 per 100,000 population) and 701 cases during the MCO3 (incidence rate of 2.71 per 100,000 population). Conclusion: The MCOs had a significant impact on case reduction. GIS is a useful tool in mapping cases distribution patterns and incidence rates during the MCOs that will assist in the decision making, and more importantly, in social mobilization and community responses. © 2021 UPM Press. All rights reserved.

3.
Malaysian Journal of Medicine and Health Sciences ; 17:7-13, 2021.
Article in English | Scopus | ID: covidwho-1573234

ABSTRACT

Introduction: Coronavirus disease also known as COVID-19 in Malaysia were reported on the 25th January 2020 until present. There were several factors that influence the distribution of COVID-19 events. The objectives of this study are to explore the association between population density and the spread on early wave of COVID-19 in Peninsular Malaysia. Methods: The clusters of districts with the largest numbers of COVID-19 infected cases and population densities were described by using cluster analysis. Then, correlation analysis where calculated to define the strength between two parameters. Results: Findings of this study showed, there was a clear positive association between population density and COVID-19 infections in Peninsular Malaysia. During the study period, it was estimated that population density has a positive impact on the spread of early stage COVID-19 in Peninsular Malaysia (r= 0.752). Findings also showed there were a weak correlation between population density and COVID-19 cases in Southern region (r=0.370), Northern region (r=0.264) and East Coast region (r=0.248) as compared to Central region (r=0.917) where it have strong correlation between two variables. Conclusion: : This study concluded the spread of COVID-19 in Peninsular Malaysia is increasing as the population density increases. © 2021 UPM Press. All rights reserved.

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